Computer aided diagnosis (CAD) tool for the analysis of calcaneofibular ligament using ultrasonographic images

Singh, V. and Elamvazuthi, I. and Jeoti, V. and George, J. and Kumar, A. (2016) Computer aided diagnosis (CAD) tool for the analysis of calcaneofibular ligament using ultrasonographic images. ARPN Journal of Engineering and Applied Sciences, 11 (14). pp. 8972-8977. ISSN 1819-6608,

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Ultrasound imaging is a cost-effective diagnostic tool to imagine the internal organisms of human beings that used routinely in the diagnosis of a number of diseases related to ligament, tendon, bone, blood flow estimation, obstetrics, etc. However, ultrasound imaging has limitations such as homogenous intensity regions, homogeneous textures, low contrast regions, enhancement artefact, limited view visualization and inaccurate qualitative/quantitative estimation. To overcome all these investigated problems, this research developed a Computer Aided Diagnosis (CAD) system that helps in efficient segmentation and Three Dimensional (3D) reconstruction of calcaneofibular ligament to enhance the diagnosis. The developed CAD system would help in the achievement of enhanced segmentation results, 3D reconstruction results and statistical analysis of the injured calcaneofibular ligament. Moreover, performance of the developed CAD system is analyzed based on the obtained results, which are indicates the improved performance with more than 92% accurate segmentation and precisely determined 3D measurements such as volume, thickness and roughness. In addition, this research opens new research dimensions for efficient musculoskeletal ultrasound modelling that makes it useful in clinical settings with accurate and cost effective diagnosis of calcaneofibular ligament injuries.

Item Type: Article
Funders: Ministry of Education (MOE): Sponsoring the project under grant entitled ‘Formulation of Mathematical Model for 3-D Reconstruction of Ultrasound Images of MSK Disorders’ (Grant no. 0153AB-I55)
Uncontrolled Keywords: 3D reconstruction; CAD system; Segmentation; Ultrasound imaging
Subjects: R Medicine
Divisions: Faculty of Medicine
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 05 Oct 2017 06:13
Last Modified: 05 Oct 2017 06:15

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